A typical task assignment system algorithmically assigns tasks arriving at the task assignment center to agents available to handle those tasks. At times, the task assignment system may have agents available and waiting for assignment to tasks. At other times, the task assignment center may have tasks waiting in one or more queues for an agent to become available for assignment.
In some typical task assignment centers, tasks are assigned to agents ordered based on the order in which the tasks are created, and agents receive tasks ordered based on the time when those agents became available. This strategy may be referred to as a “first-in, first-out,” “FIFO,” or “round-robin” strategy.
Some task assignment systems may use a “performance-based routing” or “PBR” approach to ordering the queue of available agents or, occasionally, tasks. PBR ordering strategies attempt to maximize the expected outcome of each task assignment but do so typically without regard for utilizing agents in a task assignment system uniformly.
When a task assignment system changes from using one type of pairing strategy (e.g., FIFO) to another type of pairing strategy (e.g., PBR), overall task assignment system performance will continue to vary over time. It can be difficult to measure the amount of performance change attributable to using alternative pairing strategies because the amount of performance or value attributable to a given task assignment may not be realized until a later time (e.g., months or years after the initial task assignment).
In view of the foregoing, it may be understood that there is a need for a system that enables benchmarking of alternative task assignment strategies (or “pairing strategies”) to measure changes in performance attributable to the alternative task assignment strategies over time.